{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## plot and figure 使用\n",
    "figure <p>\n",
    "    - 创建一个新图\n",
    "    \n",
    "plot <p>\n",
    "    - 画图\n",
    "\n",
    "show <p>\n",
    "    - 显示"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "\n",
    "x = np.linspace(0, 10, 10)\n",
    "\n",
    "plt.figure(1)\n",
    "y1 = 2 * x + 1\n",
    "plt.plot(x, y1)\n",
    "y2 = pow(x, 2)\n",
    "plt.plot(x, y2)\n",
    "\n",
    "plt.figure(2)\n",
    "y3 = pow(x,3)\n",
    "plt.plot(x,y3)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## subplot 使用\n",
    "\n",
    "\n",
    "subplot() <p>\n",
    "- 将多张子图展示在一起，可以使用 subplot() 实现。\n",
    "- 即在调用 plot() 函数之前需要先调用 subplot() 函数。该函数的第一个参数代表子图的总行数，第二个参数代表子图的总列数，第三个参数代表活跃区域。\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "\n",
    "x = np.linspace(0, 50, 100)\n",
    "\n",
    "ax1 = plt.subplot(2, 2, 1)\n",
    "plt.plot(x, np.sin(x), 'r')\n",
    "\n",
    "ax2 = plt.subplot(2, 2, 2, sharey=ax1)\n",
    "plt.plot(x, 2 * np.cos(x), 'g')\n",
    "\n",
    "ax3 = plt.subplot(2, 2, 3)\n",
    "plt.plot(x, np.tan(x), 'b')\n",
    "\n",
    "ax4 = plt.subplot(2, 2, 4, sharey=ax3)\n",
    "plt.plot(x, 2 * np.sin(x), 'y')\n",
    "\n",
    "plt.show()\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "大小不同的子图<p>\n",
    "- 有时候我们需要不同大小的子图。比如将上面第一张子图完全放置在第一行，其他的子图都放在第二行。plt.subplot(2, 1, 1) 将图像窗口分为了 2 行 1 列, 当前活跃区为 1。\n",
    "- 使用 plt.subplot(2, 3, 4) 将整个图像窗口分为 2 行 3 列, 当前活跃区为 4。\n",
    "- 解释下为什么活跃区为 4，因为上一步中使用 plt.subplot(2, 1, 1) 将整个图像窗口分为 2 行 1 列, 第1个小图占用了第1个位置, 也就是整个第1行. 这一步中使用 plt.subplot(2, 3, 4) 将整个图像窗口分为 2 行 3 列, 于是整个图像窗口的第1行就变成了3列, 也就是成了3个位置, 于是第2行的第1个位置是整个图像窗口的第4个位置。\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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RC7Lympqoy+fFC2xsJDEJUujZK/ci9Fw+SKHv7KR1btxm3DCrVtExBbmIGMebvcDXZJC9oAMH6FkGlZXuv8NOUZDhLm5EvAg9QAIcpNCfOEELGnpxvgCq++PHw18zPwBmptCPjlIX0avQ800bpHA1NdGF7sULzMujGzEMj95uASwrGhtJtILKimCvPBWPfnw8OM85Hk/2Gr3A5zdooffizQP0oPC6umA9eq+D18zll9P5CmoRMa6LVPRifDy6Z9v6yMwU+pMn6aLwWnHV1ZRPHLRH79VzAEjogpw0dewYDUbZrcBoRUMDxfc7O4Oxixu3VDx6IDgP9cwZYGTEu0dfXk6edlBCL6X7dZTMBJ1ieeQI5exbPe3KjoYGOtdBTTRjZyBVx3AWZN7MTKFPNQwhRLCZN4OD9GSmVIW+uZku+CDwmnHDBJ15c/AgNb5uJv4Y4fTVoOL07Ax4FXqABCUooe/ooNz+VOqShT6o3tmRI6mdr6B7Qc3N1Ph4CXUBsyqXfmYLvdcWGgh2JJ2nTHvJoWdWr6ZeSlDew7FjqZ8v/n4QHDrkfnKZkZISyrgKyqNPNQwBBCv0vF+vITiArsv+fnpAdhAcPeo9Pg8EP67R3Ezny+s1Nn8+zXDXQh8Rzc10o7tZYsDMypUU+gniOa2ppFYy3DgEIahdXZTfn4po1dfTeEOQN2EqXiBA5zkoj/7YMZrh6bSaphUNDRT6GR723y4OQ6Qi9EFm3ly8SH+pCH1tLaXMBjXekkriBjNLMm9mrtA3NHhvoQESu3icRtP95vBhyr/NtO5rKqmVTJAplqOjJIip3oQ82zOIUITXGZ5GGhrIphMn/LeruZmusfp6798NUujTCXVlZ9PihEFc++PjVA+pXmMrV2qhj4xU481AsJk3R47QDRiLef8uxxCD8GpSHdNggkqx5EH1VLxTgDz6vr5gQhFHj6Z3voBghKulJbluk1dqaqiXEkS4K9XUSiaocNfp0yT26Qh9a2v4D1f3mZkn9GNjqaVWMkHm0re0pG4XQIIXhNAfO0ae6fLlqX0/qBTLdOLNQPJc+33OOH031ZBSkDHndK6xIBc3O3qUlqVIpacBJK99v6+xVDNuGL4Ggp4dHjAzT+jTbaHnzaNBliA81JaW1EULCFbo6+poIlcqNDTQwlMdHf7alU682fg9v2/CEydomYxUhX7ePFpTJYhrjAcWUyUooT9yJLnkdio0NJDX3N7ur13pOhOzJMVy5gl9Ohk3TBCZN5cu0aBnOjchD+L5PVCcasYNE1TmTUsLhRKqqlL7fl0dxXf9bhzTGdNggghF8HyGdIX+1Cn/B4q9LmZmJqheUHMzzR1JZVAdCGc2fQjMPKH34yYMIpc+Xe+UvxuP+z8TL50xDSC4mDP3gFIZ8ATIe1y61H+hT2dgkQlC6NMNQwB0vqX09xrjWcTpnC++b/yuS+4BuXlCmBUFBeRQaKEPmeZm8gKrq1PfR2MjPaHIzxUG/RJ6wF+BuHiRehrpCD2nWAbROKYjWkAw4a6jRyn8Mm9e6vtoaCDP2c/emZ/XmJ/n7OxZmuiX7jUWxEqp6aRWMitX6tBN6KSTWskEMcDCN06qA55AMDehHz2g3Fy6Ef0Uek5xTUe0gGCE/tix9LxTgK5Rv3tn6cabjd/185z50QDxctB+3pN8jaUr9A0Nwa5GGgIzV+jTIYi4W0sLrShYVJT6Pqqr6ft+XlTpplYyfqdYtraSF+iH0Hd10Z9fpJNayQQRc25pSa7XlCoLFtD3M03oAf8F9dw5Govwo9fIY3AzlJkl9BMT1EJn6k2Y7oUuhP8e6rFj1CVetiy9/fidYumXOPjtoQ4PUyPkhxcI+H+NpWtXENdYSwv1+pYsSW8/fo9r+NEDAoJL4w0RX4ReCHGbEOKIEKJZCPGQH/u05PRpyqNP92IvKaFMD78v9nQvKCAYoa+rS22CjZHGRpqc5Ff6W6YK/YkT1Jila9eCBXSd+S1cfl1jftvF4zjp4Lfn7EeGHhDcQHGIpC30QohsAI8C+AiA1QB+RQjhcXFxl/hVcbwPvy72oSHyAv26CY8f929tbj9CXUByH36Fb1paaIJNul6g3zehX9eYEMlekB8MDdGgp1/XGM8V8AO/nBy/PefmZn96GjzuNpeFHsAWAM1SyuNSylEAPwRwlw/7nY6fQu+n58xrmvhll59rc6fy8AwrgrgJ6+tJ7NOhqIjGRvyyy6+eBuCvM+H3NTY66s81JqX/Qu/XOWtuJpFOt6fB19gMnh3rh9DXADhjeH82sc1/0p38YGTFCvKQ/Jg44qc4+OmhcjfYD3FYutTfVSz9iDczfjbavHb5/Pnp76uhIfkYu3TJ1Gvs4kWaNe1HXbLnnInX2AzPvPFD6K3yHKeN2AkhHhBC7BRC7OxIdSr99dcDX/hC6pMfjPi5wmCm3oR+2sWrWPpxE/rpBQL+Cj2LQzrpu0xDg3+PovO7Nwtk3jVWWAgsXuzfNebXmAYQ3PIkIeGH0J8FYAyC1QKYtpyglPKbUsrNUsrNC1JZRx4A7rwT+OIXU/uuGb8vdr+8wLo6Cmf4YZef4sD78eMmvHSJpvP7eRO2tvrXO/PLLj/DXS0tQFlZepO4mCVL/LvG/BR63o8fdrW309o5fl9jQ0P+7C9k/BD6HQAahRDLhBB5AD4B4Fkf9hssfsYD053Kb4RXAPRT6NOZxGXEr+5rEOLgR++M1y73W+j9uMb8mCjIBHGNpZu+yzQ0+DPg78dEQSN8TQTxHIsQSFvopZTjAD4LYCuAJgBPSikDfMq1T8yfT164X8LllzgA/nk1LS20BrnXB4Kr4MlJly6ltx+/8psZv3pnZ86ktzKqGZ5A54dw+X2N+dlo+3mNNTQAbW2UypsOfk0UZGZ4iqUvefRSyuellCullCuklF/2Y5+BI4Q/F/vEhL9eIJDMc053cpJfqZWMXx6qH8tFGPHrJvS7p8HXWLrni+P8QTgT6V5jfjdAfi2gd+xYeuvjm5nhk6Zm1sxYv/Fj4siZMzSJy++bsKfHH885U4XeTy+wstKfyUl+9zQAf4T+5EkS+3TX3zHi1zUWlNCn2ws6dsyf9F1m3jwaI9FCPwNZsSJ5E6WK314g4I/30NdHXWA/7Vq+nLxUP4TeT7v8mtbf0kIziGt8zA5ubKS4bjrXGK/J5FcYAvCnFzQwAFy4EIwz4YfQ+3m++Bqbobn0c1voGxrIGz9zxrmsiiCE3o/linnQyM+bMD8fqK1NX1DTfRCKFX4IPU+w8SN9l/HjGmPR89ujB9I7Z3yN+XntFxfTPJl0hJ5TK/0UemBGp1jObaH342LnBZ1qa/2xCUhm8KSzuqbfqZVMul5NTw/1NNJ5GpEVfkzr93OCDeNHuOvoUQobVFb6YxPgz+SkIJwcIP2lI9raKLUyiGs/3QhARMxtoffjJmxpodSydKdZG8nPp/iiH0Lv902Ybsw5CO8UoOMcG6PZzqng9yQuxo+YM4ch/EitZAoKaHJSOk5OUNdYukti+51ayfAEuHR6ZxExt4V+8WKKyaZzsaf7rEwV6T7VprmZVlAsLfXPJoAu9vZ2mvaeCnxMfgt9uoJ64QI9ccxv0Vq0iEQ13cbR7/MFpB+KaGmhh6BXVPhnE0B1mc415ndqJZNuBGBoCNi1K5JJV3Nb6LOy0rvYJyboJgxC6C+7jDz6VNPfgghDAOkPFB89mjzvfnL55fR6+HBq3/fjeaxWpJtiOTxMjyT0W7QAf4Te73oE0m+0ObVy6VL/bALSHzvbuxfYvBl48UX/bHLJ3BZ6IL2Y86lTtNIki4yfrFxJccbz51P7vt+plYwfQl9fn/76+GYWLqQUy1R7QUGFIYD0ZnseP06NfRBC39BA19fAQGrfz2ShX7bMv9RKpqYmvQhAUxO9BqEXDmihT2fiCItKUKEbILU4/dAQxRGDuAnTHcQ7ciSYMIQQdAOl49FnZfnvBQLJFMtUBoq5/oM4Z3zdptI4jo2RoxOEM8HXbapCH0TGDZB8UluqQn/4MC0O6NdyER7QQt/QQLHZCxe8fzdIoU/nJvRz7XIzJSX03NJUhF5KEq4gzhdA+03Vo29pIZHPy/PXJoDqYXQ0tYHioAYWAWDVKnpNpXHkDKcgrrHCQspiS0XopQwmfZdJZzb94cNUj373NFyghT6dAZbDh2nGnJ9pb0xtLQ3ipeLRBxVvZlKNOXOYIAjvFCCP/syZ1EIRfi5payad7K6jR2lQvbzcX5sAsisrKxlS8MKhQ/S6Zo2/NjGpZt5cuED1H0TDCCTtSuUJcE1NkYRtAC306d2EnHHjZ9obk5VFF1UqHmqQ8WYgdaEPKuOG4ZvIa+Po99rlZtKJOfs9w9NILEbHnI7QByVcqY5rBJVxw6xeTaFRr88YGBmh8J0W+oior6fueird18OHg624lStT8+ibm2mCjR/r41vR0JDa2tx8LEGGbgDvddnWRqtyrg7mUcdYvJjmRqTq0QclWgCFb1IV+iVLKJQXBI2N9PQqrw8K58YhqN4sXyPc0LmlpYVCXRwuCxkt9Dk5JBAHDnj7Xk8PdRODEi2A9n38OMV3veDnU5Ks4JvI69rcR49SOMrPtWSMcCjCq9Bz3a9d679NQDKd1KvQc9ZVUD0ggITn2DHvsz0PHQquYQRS7wUFlVrJ8DEf9LgSe4QZN4AWemLtWu9Cz2GIoD16XgbZC01NwYoDC73XsNKRI3QD+7mWjBGeUezVLr5pg4o3A6nFnIMOQwAk9GNj3sao4nFqTDNR6Hm9oqAGPMvLyVHxKvTsfATpGNqghR4goT91ytvDDoLMuGFYrL0IV3c3cPo0sH59MDYBdIML4b1xDDLjhkklxfLAARpQr6oKxiYgma3hZRAvyNRKhkMJXsI3p05R2C5Ioef1nlLx6IMK2zCrV3sP3Rw+TKGu4uJgbHJACz2Q7LJ7qbzDh8lrCGoAD0gtl37/fnoNUugLC8nj2rvX/XfGxijUE6RoAST0R496E9QDB8ibDyrUBZD4jIx4S7EMOt4MJHukXoSe75MghT4/n4TRi9AHtWqlmTVr6Hx5ucYizLgBtNATLPRePNQjR6iLmJsbjE1AMnUzFaFfty4Ym5j164F9+9yX5wlDQQv9ZZclJ4y5QUrqhgcVn2c4LMT144ajR2kgt6goGJsAWguppiY1oQ96YNFruCvo1Epm9Wqae3PqlLvyUpJjGNFALKCFnqivJy/Vq9CHEW/zOglo3z6KI/q5bLIV69dTKKK/3135oDNuGK9r3pw5QyG7oIWee1h79rj/TlCLmZnxmnlz6BAtOeH3YmZmvC5XzHHzoK8xbrTdxulbW6kB0h59xGRlUeW5FXpezCyMivOaYrlvH4lKkGEIgH6DvWE3BPGUJCu8zijmOg9yIBYgz7mhwZvQB51ayaxaRQ2j22VAgs64YVatovTK1lZ35XfvpteNG4OzCfCeYhlxxg2ghT6Jl8wbXswsLI/+wgV3S7bG4xQaCDI+z/BvuA3fHDlCYah584KzCaAB1fJy9x59GBk3zMaNwHvvuSvb0UF55GFcY6tWUc/MzfiBlOEJ/aZN9Lprl7vyu3dT7zyo+SNMeTmF1Nw6OXwt6tBNBrB2LQlqZ6dzWa64sDx6wJ1Xf+oU3bBhCP3SpTRZxq3Qh5FxA1BPxku468ABummDboAAYMMGGqvo6XEuu2MHvbLYBYmXzJuzZ+kaC0PoN2yg3rZbod+1C7jyymBtYtasce/RHz5MExirq4O1yQYt9IyXuFsYqZWMl9meLLpBD8QCdAOuW+dO6KUMPrffiJcUy4MHw/HmgWRIwY1Xv307NVqZJvRcJgyhLyqi39m507lsTw/F88MSek6xdJN5wxk3QYdTbdBCz3jJvDl8mLqHQSxmZqaxkWaTurnYWXSDHlhkOPPGKbZ78iQ9Meh97wvFLFx+OXDunPO8iIkJulnDOl9ehH7HDhKToJYYMFJVRQOrboQ+rIwbZvNmuvadrjE+p2E0jAA5B24zbyLOuAG00CdZvJhib26E/tCh8Ga45eYCW7YAb77pXHb/fsrrD2tSxvr1NEHLKbb71lv0es01wdsEuO8FnThBqZhhCf3ChdR9dxqQlZI8+i1bwrFLCPeZN4cOkZOzYEHwdgEk3O3Na2dkAAAgAElEQVTtzgOyHN4JeiCW4V6gU/imp4eWsYhwIBbQQp9ECHcDssPD5G1ddVU4dgEkkHv2OC+/yxk3YeF2QPatt6jxCUtQufv+7rv25cIciGU2bnQW+pMnaawoLKEHSIjcCj3PjA6DzZvp1alHu3s3zQcIKw7uds2bMMfzbNBCb4SF3q6buH07Zdxcd114dl17LYUZeIDOisFBSvkMIz7PsHA7Cf3bb1PDmJ0dvE0ADRTX1wOvvGJfjhv1MOLNzMaNJJYjI+oy27fTa1ihLoA8+o4O+2SEMDNumCuuoOvGjdCHFbYBkpk3Th79O+/Q64YNwdtkgxZ6I2vXUiji3Dl1mVdfJW/mgx8Mz66rr6ZXDoFYwQNDYXr0ZWUkqHZC399PSyWEFbZhbriB6spusOzAAbI/jDg4s2EDrRRp5wnu2EFrxYfZaHMP9bXX1GUuXAh2OWcrCgqox2Un9P395DmHNRDLrF7t7NFv20bzJ4JaTdMlWuiNsIdqV3mvvko3YBjpeMy8eeRx2cXpw1jjxgqnpRC2byexjULoOzvtPa4wM24YjiHbhW+2b6dyQTzWUMX7308N3s9/ri7z8svJsmGyeTPF4FU97b176bOwhZ5TLMfGrD8fH6de5Yc/HKpZVmihN8I3vUq4RkfJq77++vBsYq69lkIgKg913z5axoEf3h0W69dTuunwsPXnb71FPaCwxYHrSBW+GRoiLzCscQOGB8tVmTfj4yRqYcbnARr0v/FGYOtWtaA+/zwNwoYZUgJI6Ds7aVVWK3hGbJihG4CcicFBdS9oxw7K/NJCn2FUVlLGxvPPW3++cycJRBRCf8011G1WZZLs20cNVVhxcGb9eho/UA3kvfUWdXGDeOapHfX11F1+9VXrz//7v8kTu/nmUM1CVhbFnVUe/aFDJB5hCz0A3HorDQRbrS8zMUHn7LbbgnuegAoWcFX4ZvduGoRdtCg8mwC6dvLzgWeftf582zZ6/dCHwrNJgRZ6M/feS+Jw4cL0z1g0whyIZa69ll6t4vQDA9TdD9ujAZKDTFZ2xePUCwk7bMPccAN59FYe6lNPUcMeRaO9cSOFG6x6ZzzgHrbXDAC33EKvVuGbd9+lJRk++tFwbQLImcjJUc+Q5RmxYU9IKioCbroJeOYZ62vsxReprsOYb+OAFnoz995LN+CPfjT9s9deI+80rBxiI42NdMFYxemffpoGpO67L3y7GhroRvze96Z/dvgwDW5HKfRWcfrhYeAnPwF+4ReCexKRHRs2UH1ZLcG7fTv1foJ+eIYVK1ZQ6M9K6J9/nnqLt94avl35+TQuZuXRDw1R/Ubh5ADAXXfRpClzuHdggJycDAjbAFrop7NmDQ18Pvnk1O3j48Abb0TjAQLkrVxzjbXn/N3vUkPAXn/Ydv3mb9JNaI47hz1RyowqTr91Kwntxz8eukkAKBYuhHXjuH07efNhh0eYW24BXnpp+gDjc8/R9RV2CI5RzZDdsYPCSmEPxDJ33EF1aQ7fvPEGjelpoc9QhCCv/rXXaEYbs2cPiUNUQg/QjXb0KOU7M83NZOuv/3p0a2ncdx+lA37nO1O3v/UWzaIMY6ldK+rrgbq66XH6p5+mTKaoYqfLlgG/+IvAP/3T1FVJ+/speyqK+Dxz661kx9tvJ7e1tlIjHkXYhuExqq1bp27/q7+iuoxKUBcupESDZ56Zun3bNhrgDjMN2wYt9Fbcey95Dv/5n8ltLBZRCj17xkav/nvfI+/vV381EpMA0I12zz3Av/0bdaUBOn9vvEE2R9UACTE9Tj8yQt7X3XcH+3QwJx58kKbHf/ObyW1f/CJ5p1EK6oc+RCEaY/iGkxNuvz0amwDgk58kh+Hzn0/2Nl5/nQaIH3qI1vuPirvuonEC41Ig27bR/Jcgnw7mBSllyn8AfgnAQQBxAJvdfm/Tpk0y41m7VsoPfpD+Hx2V8oYbpFy5MlqbhoakLC+XsrFRytZWKcfHpaytlfIjH4nWLiml3LZNSkDKxx+XMh6X8vOfp/ff/Ga0dn33u2THzp30/ic/ofc/+1m0dkkp5Y03Srl4sZTDw1K++qqUQkj5e78XtVVSXnutlO97X/L93XdLWVdH9Rolzz5Ldff3f0+2fOADUi5aJOXAQLR2HTxIdj32GL3v7KS6/NKXfP8pADtlKlqdypcmvwysAnAZgFdmndD/xV9QZT39NIk+IOUjj0RtlZRvvCFlcTGJPYvYk09GbZWUExNSLl8u5Yc+JOX//t9k1+//fvTicPaslEVFUhYWSvnnfy7lvfdSYzkyEq1dUkq5dSudp69/nc7d8uVS9vVFbRUJlBBS/tEfSfmP/0jn73d+J2qr6Fq65Raqvx/8gM7do49GbRXZ1dBADc/XviblVVeRbW+84ftPRSL0kzuZjULf1ESnB5ByyRIpn3kmaouSvPmmlCUlZNu8eeQRZgJ/+ZfJc/Zrv0binwkcP04Cb7QtE4jHpdywgUQVIK8+EzhyhJybWCx5zrZujdoq4uBBKbOz6ZzV12dGgy0lNYp8rtaulfKv/zoQJ0cLfRD8j/8h5f/6X5nhZZl56y0pS0ulfPDBqC1JcvYsec4f/7iUY2NRWzOdN9+U8pd+Scq9e6O2JMm//zvdhp/7XNSWTGdiQspz50hco+6ZGfn936dz9v3vR21JkvZ2Kb/1LSmbmwP9mVSFXtB31QghXgSw0OKjP5VSPpMo8wqAP5ZSKlceEkI8AOABAKirq9t0ys2C/Rp7BgcpxziqVDwrLl6kwdkIn6Yzo5CS0hk/+MFw17aZyQwO0mDnRz+aWdd+CAghdkkpN3v+npPQu/zxV+Ag9EY2b94sd7p5YpJGo9FoJklV6OdWc6jRaDRzkLSEXgjxC0KIswCuBvCcEGKr03c0Go1GEy6+hG48/6gQHQBSDdJXArB5DM6sRB/z3EAf89wgnWNeKqX0vNhWJEKfDkKInanEqGYy+pjnBvqY5wZRHLOO0Ws0Gs0sRwu9RqPRzHJmotB/07nIrEMf89xAH/PcIPRjnnExeo1Go9F4YyZ69BqNRqPxgBZ6jUajmeXMKKEXQtwmhDgihGgWQjwUtT1BIIT4rhCiXQhxwLBtnhDiBSHEscRrRZQ2+okQYokQ4mUhRJMQ4qAQ4nOJ7bP5mPOFENuFEHsTx/ylxPZlQoh3E8f8hBBi1i1+I4TIFkLsEUL8NPF+Vh+zEOKkEGK/EOI9IcTOxLbQr+0ZI/RCiGwAjwL4CIDVAH5FCLE6WqsC4XsAbjNtewjANillI4BtifezhXEAfySlXAXgKgC/l6jX2XzMIwBulFJeAWADgNuEEFcB+CqAryWOuQvAZyK0MSg+B6DJ8H4uHPOHpJQbDLnzoV/bM0boAWwB0CylPC6lHAXwQwB3RWyT70gpXwNwybT5LgDfT/z/fQB3h2pUgEgpz0spdyf+7wOJQA1m9zFLKWV/4m1u4k8CuBHA04nts+qYAUAIUQvgowC+nXgvMMuPWUHo1/ZMEvoaAGcM788mts0FqqWU5wESRgBVEdsTCEKIegAbAbyLWX7MiRDGewDaAbwAoAVAt5RyPFFkNl7ffw/gT0CPHgWA+Zj9xywB/FwIsSuxVDsQwbWdE/QP+IjVAuc6N3SWIIQoBvCfAP5AStkrZvl69lLKCQAbhBDlAH4MeizntGLhWhUcQog7ALRLKXcJIW7gzRZFZ80xJ7hWSnlOCFEF4AUhxOEojJhJHv1ZAEsM72sBnIvIlrBpE0IsAoDEa3vE9viKECIXJPKPSyl/lNg8q4+ZkVJ2g57QdhWAciEEO1+z7fq+FsCdQoiToLDrjSAPfzYfM6SU5xKv7aAGfQsiuLZnktDvANCYGKXPA/AJAM9GbFNYPAvg/sT/9wN4JkJbfCURp/0OgCYp5d8ZPprNx7wg4clDCFEA4CbQ2MTLAD6eKDarjllK+QUpZa2Ush50774kpbwPs/iYhRBFQogS/h/ALQAOIIJre0bNjBVC3A7yArIBfFdK+eWITfIdIcR/ALgBtJRpG4A/B/BfAJ4EUAfgNIBfklKaB2xnJEKIDwB4HcB+JGO3D4Pi9LP1mNeDBuGyQc7Wk1LKvxBCLAd5u/MA7AHwKSnlSHSWBkMidPPHUso7ZvMxJ47tx4m3OQD+XUr5ZSHEfIR8bc8ooddoNBqNd2ZS6Eaj0Wg0KaCFXqPRaGY5Wug1Go1mlhNJHn1lZaWsr6+P4qc1Bnbt2tWZyvMnVeh6zRz8rFtdr5lDqvWattALIZYA+FcAC0FZE9+UUv6D3Xfq6+uxc+fOdH9akyZCCOUD2nW9zmz8rFtdr5mDXb3a4YdHz4tS7U7kjO4SQrwgpTzkw7410aHrdfai63aOkXaM3mZRKs8Mjg2ic7AzXZMsOXrxKIbGhnzfr5QSF/ov+L7fVOzwM1XWz3rVZBa6bucevg7GmhalMn/2gBBipxBiZ0dHh+X3b/u327Dg/7oPP41OjGI8Pu5YbmhsCBv+eQO+9s7XXO33RNcJxGXcuSCAR157BIv+dpErsX/15Kv4wotfcC3I9z51L/7s5T9zVTbnkRx89vnPuirrlXTrVZO5qOpW1+vswjehNy9KZf5cSvlNKeVmKeXmBQusxfz1068DAFp7Wx1/79kjzyL2lzE8+MKDjmWPXDyCofEh7Lmwx7Hsqe5TWP715djyrS2uGpFHdzwKAGi51OJY9jee/Q185c2v4J2z7ziWvTR0CU8degqPvPaIY9m+kT7EZRyP7XzMsaxX/KhXTWZiV7e6XmcXvgi9YlGqlNlxbodjmS+/TqsfvH32bceyhzoo9NjU0eRQEjjRfQIAsOv8Lrx26jXH8u0D7VO+Z0dtaS0A4Bvbv+FY9qdHf+pYhjnTm1y9+dKQfzOp/a5XTeag63ZukbbQ2yxK5YmR8eTyFjvPOY/ws8AOjTvH3Vnoj1065uil837N/1vRNdQ1+f+JLmeh7x0hp+mN0284lv1Z888AAAICYxNjtmVP95ye/P/lEy877tsNftWrJvPQdTv38MOjvxbApwHcmHgu4nuJxcc8caonmTXkxqPnQdu2/jbHsiz0oxOjjoJs3J/TwPDu87sn/3fj0Z/vOw/AndfN4SsJ58Feo9DzsfqAL/WqyUh03c4x0k6vlFK+AesHCHjieNdxAEB1UTXO9p61LTs8Poz+UXoSW8dgB+IyjiyhbrMOdRxCTUkNWvta0dTZhMb5jcqybQPuhZ7LVhZWOgr92MQY2gfakZOVg4GxAYyMjyCWE1OW7xruQkFOAYbGh3Cm9wyWlC1Rlj3dcxrZIhu52bnoGu5SlvOCX/WqyTx03c49MmYJBBb6KxddiZ7hHtuyLMBrFqzBeHx8SgjFita+Vlxffz2Aqd6vFW39baguqsb8gvmOQs+/u3HhRueewkAbJCTWVa2j7zoI8qWhS1hXTWWdGr7TPadRW1qLysJK34Reo9HMHjJG6M/2nkVuVi4ur7wc3cPdtmVZgFcvWA3APpY+EZ9A/2g/6krrAMCxEWkfbEd1cTUqCyvRMWifVsZ2bli4AWd6z9imZJ7rowfnrK1aCwC4OHjRdt9dQ12TjYIboa8rq0NFfoVjo6fRaOYeGSP0PcM9KMsvQ0V+BQbGBmwHIDsGSIDXLFgDwF7oeQC0qqgKsewYekbshZ49+srCSkePvnu4GwU5BVhYvBBxGZ8MJ1lhFnq7OP3w+DCGxoewvGI5CnMLcabnjLIs77umtAYVBRWOjaRGo5l7ZIzQ9472ojRWivL8cgCwFeTJ0E0VCb0xrm6G91OWX4ay/LJJ4VfRNtA26dG7EfqKggqUxkrpGGz27UXo2SufVzAPVUVV6Byyt6NnpAflsXLy6HXoRqPRmMgYoe8Z7pki9HaeKYdU3Hj0HKopi5WhLFZm24BIKdHW34aqwip3Qj/SjfL8cldCz8K+cv5KAMDFIXXohsvOK5iH0lgp+kb6bO3oG+lDSawE5fnlOnSj0WimEckyxVb0jvSiLFbmSug7BzuRJbLQMK8BWSLLNsXS7NHbxegHxgYwND6E6uJq5GbnonOwE1JKUNrxdLqH3Qt930gfYtkxVBdVA3Dw6BNeeUV+BUryStA3qhb6sYkxDI0PoTRWirGJMe3RazSaaWSMR9870uvao+8c7MS8gnnIzc5FWazMtqwXj56Fujy/HJWFlRidGLWNu3cNdbkX+lHyuovzipGTlWMr9EaPviRWYuvRcyNQkleCioIK9I/2u1q6QaPRzB1mrNDPL5gPACiJlaB/TC3GXjx6FtTivGJUFlYCgG3mjSePfrQPJXklEEJgfsF826wbDr9w/N+ppwAApbFSVORXTNql0Wg0TEaFbtwKfd9o36S4FucV23q8Xjx69t6L84oxEZ+g37LZd/dwN8pjSaF3akRKYiUAyFO/NOxP6IYbgdJYKXKzc+n7Q12TDZVGo9HMSKHvH+1HcV4xABJlu/CK0aMvjZXaijHvpySvZDL8odq3lHIy66YsVjZ5DCrYowdI6O08+ktDlyAgUJZfRkJv09jwb5bESpCfkw/AeTKWRqOZW2RE6GZkfAQjEyMojZWiOK8YWSLLtdA7ebw9wz2IZceQn5OPslgZ+kb7Jr11M7yf4rziyf2rhH5gbAATcgLl+eWTZZ1CLOzRl8ZKXcX+s0QWZd2M9iknY7HNxkZSZ95oNBojGSH0LJBlsTIIIVCeX+6rR1+WTx43v6oahkmPPjFoatxmhu0rzy9HdlY2ivOKXXv0RXlFtjbznAK2BQAGRgesyxpCNxUFFKPXHr1GozGSUULP4uZF6EtiJc5Cnwit8KsqfGMcjPUi9Gy7o0efEHqnxsncYwHUjdNk6CavZPL82e1bo9HMPTJS6N0Mmk569LnOg7Fmj14lyMYYvZPQc2PBNpfGStE76pxeyTYPjFl76AB570V5RVP2r7LZmHVTlFtka7NGo5mbZMRgrFnoi/OKlaGKuIxjYHTAW+jG7NErGhHeT1FeEXIncqdsM8NCzeJq59FLKdE/2u86dDMwNjClxwKos3/4N4vzijEhaexBde40Gs3cJCM8ehZeFvqivCKlxzs0NgQJOUUIh8aHlJOEOJsHSHr0ytDNaB/yc/KRk5WDgpwCCAi10CfE1Oh5q4R+cGwQcRlPevR5xRidGFUu3NY/2j+lAWHbVMdXlFuE7Kxs5GXnTa53nym4fA66RqMJkIwQ+snB2IQQF+WqPV5jrrvxVeXFGsMgk2UVQmj0uoUQtr0FLx69cfaq8TsqO4w283fs9s2NAWDfGwqTgweBVauA1193LislsGcPMGb/xMRJnn0W+Oxn3ZV96y3gpy4fvysl8Jd/Cbzt/BhijI0Bv/u7dJxuuHQJ+PGP3TV827YBn/oUMGGdHDaF7m5gXE+E1jiQUUJvDG2oxEol9HaCzMI6KbCKffeN9k3uj/ftxaN3GuQ1evR2dvSP9qM4133oxij0do1kmCxdCpw4AfzIxWOnn3sOuPJK+s7goH3ZeBy46y7g0UeBM/arNwMA7rwT+NjHqHFw4qmngC9+Efit33Iuu2MH8E//RHY7iXdPD1BdDdxzD7DT+XHIeOwx4PHHgRdfdC77+c8DK1Y4l9PMbTJC6FnwWACLctWhG7PQO2WlDIwmhb4wt5C22Xn0CWHl31Atr2D26Itz1Y3CNI8+z37QdGBs+mCsXejGaLNd2CtMiouBW28loXcSwh2JRwSfPw/s329f9qWXkv9v22ZfdnwcuJiYl/Z3Lh6B/cgj9NrlIjv1zTfpdXQUeMPhWe8vvZT0unftsi87Pp48rm9/29mOpiagocG5nGZukxlCnxCmgtwCAAmh98Gjl1JicGxwUjT5VenRj6Tu0RflFWFwzNodVXn0KpuNjZOb0A2XAewbybC55x7yut97z76cUdwPH7Yv+8orQFYWUFrqLPRNTfSamwscO2ZfdmICOHIEKCgAzp0DWlvty7/xBjVmALBvn33Zo0fpNTubQlR2vPsu9QBqaoCtW+0bSSmBQ4eA1avt96nRZIbQjw6gIKdg8gHfRXlFGBofspwNqhJ6q9DG8PgwJOSkaPIAq5sYPe/bzuvmwU+ABHZkYsRy1q2XGP3IxAgm5MTkceXn5CNbZCtDN8aGDLAPe4XNpk306iSy+/dTOCY3NynOKk6eBOrqgJtvdo6lc5jkl3+ZxHvA5rScPUtx9/vuo/d2+5aSYv8f/ziQn08hKjuOHaPQzfXXOws923zffUBfH8XgVbS2UplVq+z3qdFkhNBPE6uEEFp5yNNCNwkv2UqQWUg5ZCOEQGFuoX1s3KVHb8yMMf6GlXgbZ9wabbe02dRTEELY9hYGRgcmf9vJ5rCpo8f04rTN89gHBoCWFmDjRgpBOHn0J08C9fXA8uXUW4irH9OLPXuAoiLg9tvpfUuLuix/ds899Go3yNrdDXR2AuvXkx3Hj9vbfPQosHIlHeO+ffaDp2fOUOOxZQu9P3lSXZYbRe3Ra5zICKEfGJsqVnYhFi+hG7No8v/KEIvFYKwym8cQRzf+htW+J+3IdQ4hmWP/ADUiKpsHxwanlM2k0E1pKVBWZi/0hw+Th7x2LXmmbjz6+npgyRKKj3faPATs9GkS4ssuo/d2PQsW69Wrgaoq+9ANf1ZT403oL78cGBmh3oWKM2fo2Orr6f2pU+qyhw4lbdZo7MgYoTeLFW8342UwViWavoRuRgesPXo78TaleVrt23x8bL8yFdN87jIodAOQV28nViyaS5eSILe0qD1eFsn6eqC2lradPave97lzwOLFycFKO6FvaaHQUW0tfcdOjPk3a2qAZctI6FWx9N5eoK0NaGwEFi2ibefPq/fNQr90Kb238+ibm6kxXbBAXUajATJE6K3izIA3j94qhm3p0Ttk9BjLOsXozWLM282wN86NgV1ZK5vtPHpz6CaTPHqAhN7Oo2fRW7SIhHNiQu2lnz5NgupV6FkMnUI39fU0YFpT482j7+tLZveYYaFevpxsYbtUsNDPn09hJ7tG8sIF2qfiSZcazSQZIfRWYgWoPXoBgYIcytDh71mGTCw8epXHOx4fx+jE6LSeha1H7yF0kyWyEMuOAXDn0bvphUzEJzAyMTKtIcuUGD3gTuiFoHDJwoW07cIF67IsmsuWkRgCaqGfmEgKIUCvqv0CZCOHS9wK/eLFZAugHpDl31y0KOnRq4R+fJzOR20tnZOlS+09+gsXkudMo7EjM4TeIvwAqD36oryiyQd252bnIjcr1zY27sbj5e+bPfqx+BhGJ0YdbbYL3QyODaIwt3DS5vycfMr+sQnzTOktKMYVzD0F/t7w+LByzf2wqaujWaH9irbn/HmgspLCJk5CzxOkliyhhiEnRy30HR0k9iz01dUUQlHR1pb8/Zoa+v7IiHXZ1lb6/by8pHir9s3bq6upV5GdrQ7dXLhANnMjtnSps0evhV7jhowQelXWjWVowxQyAdShDSvxVmXdqEQTUA/0erHZuF+75RVUoRs7m60aSVWoJ2ycPO/z55Ni6ST07e30Wl1NufQ1NerZsew1uxF6Kemzqip6X1Njb8fZs8ky/B03Qp+dTa8qj97YkAF0XviYrbhwIXnuNBo7MkLop4VubDx69o6NqGaDqkI3br1/p7CQlUevanCMZdkOt6GbolyFzWPWPRbjZ1FTXU2vHYpnrBvFisuqBLatjSYpFSYOt7ZW3YCohN5q0HRgABgaSv4+f0cVvmltnS70KkG+cIEmYZWUJPetEnrebtx3e7u1zf399Kc9eo0bMkPoPWTdWAm9yqP3Mhhr5R3bCv2o+3CT2aMH1MsrWIVuVDF6qx6L0/IKYcMZISohNHr0xcX0p/KO29uTwgqQMKv2ayX0IyOUBWPG6HUDSaFVCT0P8gLU6NjZ3NZG++UB00WL1KEbPhY+xqoqmsTVY7GEEv+eFnqNGzJC6M3i7dWjVwq9lUevWF7BKnTjJN5uQzfm0BSX99I4ue2FOC2YFjZ2Hm88Pj38sHChfejGKPQLFqh7CufOkbiyeLMgWgkyb+N983esbOasIC7D5VUNjjH2D9h79HwslZVT7bHaNzcWWug1bohc6OMybjnpB1DHu6eFQRReOosdr6EDOId53IRuJuITGB4f9hS68dI4GTN0uKzrGH2GhW5YtKwE+eJFyjRJR+gvXrSeHdveDsybR4O8gH1YyBj7Byi1UWXzpUsUSjHmrldVqT36CxemNwqdndZzBdrbgYqKpM12Qs/HoYVe44bIhX5obAjAVA82LzsP2SLbF4/euIYOlx2dGJ32oBLVwK3xM7uytpk0o9NDN3ZjBUW5yawiLmu1jo5ljD7DQje5uSReVmJlDlUA3oU+HifxNdPZOVWMWWztPHouk5NDjYSV0PM2877tPHqj0PP3rPLuOzqmNyCAFnpN+kQu9FYhE17fxY8YvVXIhD9zskPlHVsNmPI6Om4HY+28dKvjM9poPD5gepgHSDagmQAPKppRiaaVGMfjVN4o9HZC2NGR7E3wfgF7oTfaoQoLWdms8ug5zGMUY/6eat9uhb69nUJT3PvQaOyIXOit4uj83k1aI6CeBDU4bp3tAqhF003oxqpRmLTDRXolf9eyURi3yCpSLPJmZYfTmvtRoBJNngFrFLfKSloP3vy0qa4uEk6zRw+4E83KSkrJtBJkc5jHzmZV49TZOf2JUBxWsrLZavavucfCDZWV0Hd2kshnZ0//TKMxE73QW3ilgH1ufGGOSTRzUvDox6w9ejdxd6vQDX9XORhr0ZC5tVkl3qq1fKxsjhInj97oebMQmsMx5ji6sawboc/OJjG3ElhjDr1x3148eimn79uqrBeb7cJe5h6LRmOHL0IvhLhNCHFECNEshHjIy3ftvGM/Bjat9gtMD914GYxV9ULsQkhWNrsNTals9pop5JV06tVIKkJvFkL+vpVomvcdj5M3bV7sy068vZQ128yNhLm8l+OLx6ePK/C+VecuncXM/KpbzaiW65QAABnuSURBVMwgbaEXQmQDeBTARwCsBvArQgjXC6d6Ec24jGNofMg6dKPIurHar/F3Gf4tc4YO78eqrGXoxlSWbXYdukkhRm+02S+PPt16NcLZMebQRkcHUF4+NWTComj2jq0GblUZPRzmcSveVgKryujxYrNVaIpj6uayly5ND/MAaqG3stktftatZmbgh0e/BUCzlPK4lHIUwA8B3OX2y1axccA6DMIDjFZCqMqkUYVurMIx5gydWHYMAsLVICjbobLZyg4rm1Xpo/xZqjanQFr1amTBAgptmDNNOjunhx9UHq+Vd8yhDTdl+b1V6Ebl0U9MTH9+rKqsF5vLy9VlvfQs0gjd+Fa3mpmBH0JfA8C44sjZxLYpCCEeEELsFELs7DBcuap4t5XHq/Kk+b0508TOO54WurEIr6gyaZQevcVkLD9ttgohmc+bXcaSR9KqVyN2oQ23oskCbdUwmD1eL6LJYR4vDU46Qq+ywyo0xd9V2ZxG6Maxbt3Uq2bm4IfQW62GPW11DinlN6WUm6WUmxcYrtCPrvwomn+/GY3zGqeUt4rR2wksYD1Y6Tbrxirbhcu7GbhV2WwXmrKy2VPjZDEGweV98OjTqlcjXkRTFdqwCpkA1IioGgU34Ri7MA8wvRFpb0/fZiuh5/dWg8Jmm7u7rW32gGPduqlXzczBD6E/C2CJ4X0tAJtHK0ylMLcQK+atQCwnNnV7zvQ8cyfRtGoY3DYKVmEe3rdKvN0MsNrF861sthpXUDZOFtk8gDqjxyNp1asRO6E3e7t2oQ0rvbETTSvvOB6fGo5R9RTseiFmMVbZbBWaYrvcZOjwe7PNqp6CB3yrW83MwA+h3wGgUQixTAiRB+ATAJ5Nd6dePHq7wUq3jYJV6IbLe+lZpGuzrUdv7rFYpGJyeR9CN77Vq5XQczqiSrythFAlmlZet/F3zXYY920nsGabVZkxXN5t42Q1wGoX5jHbobLZA4Hcs5rMJW2hl1KOA/gsgK0AmgA8KaU8mO5+vXjHVqJpl6EDWGfSWIZubMTbmO3CZa1i/8bfNdtsLK/K0FHN5g0ydONnvVqtHdPTQ5OirMTKKi5tJ5rm0EZ7Oz2UPDa1k+hJNK0mK1lN2jLu202PhW3u6JhusyrMY7ZZ1QtxS1D3rCZzyfFjJ1LK5wE878e+GGMmTU4WmakSTSvxVmXoKDNpxgZQkV9haYeVJ23OduGyvCZNdlb25H6t7LDK/lFl6HCDYtULqSqarjqqOQhe8aterbJjrCZAMVVV0x/N19kJbNkyvaxxvRujOFuJsVU6psqTzsubPlnJKsXTaIeVzZs3Ty9bVZXM6DE2gqr9mm22s8MtQdyzmswl8pmxKqzWbPHi0asGTFVZKSqPXhW6sQqZWMXSJxsnFyEk1fFliSxlD0cZusmQZYoZs8drXkjMiHntGKcwDzBdCN2Kpmrglu1wGzIx90KktO+FsJ3Gfbs9Pl7QLB2h18wtMlboreLSXoRe5UnztnRi9KqQidVA7+QAsotlDVTHx/u2Ct0EOBjrKyqhtxKrhQuTz3wFkmEeVRgEmO552wm9WWCLioD8fOvyXjz6zs7k06B4vR6r1SW9CL1VL6StjXobeXnTy2s0VmSs0Ft5x07plcZF0FT5+VzeTSomf98qnq8qC0wNIak8ekvvX5FVNGmH1WCsRVmf0it9xSz0dqGb6urkwCdg70l78ehjMVrvxviEJ7sHbJsHTe3sqK4mYefsGLtlhL0IfSwGlJZOHUA2L32s0TiRsUJvNVipXOkyz8KTVsy45W1WHr35oeOA9YJpdmEe/nyazQqP3k1DBqgbJ5UdmbR6JWDt0Qth7aWblxS2e2yeWeh5aWBVWMO83r3xUYZmzKEbFmYrm9k2bkT4N1ShKeP+uFFT2WwOZWmh13glY4XearBSJd5Wj89TxeiB6V66lNI+3u1SYC1DNwqbvQq9Oe4el3F6ypWix5JpHn11NYkmP1mpvZ0GInMs0gHMQm9+/qsRc3bMxYsUPnEr9OZHGRrhcAyHkDo6pi9nzPA+zEJv1TjNn0+NHB+fatIWY378oBZ6jVcyVuhV3nFedh5ys6feaQU5BfR0J4vYuBuPfmh8CBLSslEozivG4Ngg4jKZC+c0GGvuhagydKaVVWQV8TareL5d6EbK5GTHr7zxFfzLzn+ZVjYsamrIczV66SqxMj/flUXOSpBzc0l8uaxTRopXj964Ro/VrFjGLPR2vZDsbGqg2Fb+jup8aKHXpEvGC71R3PpH+y2FjdekSTVGP/nEKBvxNmb/2A3cGn+by1rtN0tkIT8n31PoxjKbR9ELAagBYx7f/zi2tmydVjYsahIrqbS20qsqjg5Mf77ruXM08DhvnnX52lrg7NnkfgFnoZcSGBwEenvVMXqzHefPq8taefR5eZQbb4Ux/s+2L1liXZaFXkpgeJhs1kKv8ULGCr1qsNIqjg6Q523lHavWr7ESTat98zZzI6LKdmE7jTZbleXyVo2Tcs0dF+MVXNa4P7Zfde7CwCz0dl5pSQllwbBXfP48iZ2wWqEFJJBnziTLAmpBXriQBL6/PyngKo+ehZf3feYMUFentrmoaKrQV1erba6uTv4+C31trXXZxYuTjZJdWqpGoyJjhd4qtGEnVl5DG25FUyX0KjE2/jbv28rr5n27DTeZeyFO8fxpdigGm8PCKPRSkiCqxEqIqc+OPXfOOj7PGD36kyfpVSXI3ABcuJAUZZXQ8z5On6YY+tmz6v3yfoxCb/fg7ro64NQp+v/sWTpmlR187OfOaaHXpEbGCr1qMFYlmmYhdBJNt2EQL166Ku6u8uiL84qnNCB2PQtzHr0rm102kmGwYAHF01tbaVBzYABYvlxdftGipPd/7pxaBAHyvDs7gaEhEs+qKqBwerUD8Cb0CxeSzadPU9mJCXV4hffjVujr6+m4RkZI6Kur1XnxRqHn3kXNtAWjNRo1GSv0Vl6pnViZRdMxg8UiRu8mdMMZOl4mTNl59Eab+0b7puxnyr7zrBsyu9AN73siPkHr/iganDDIykqK9/HjtG3FCnX5hgaguZn+59CNCg55tLaSR19fry7L+zlzxj4zhm1esoQaj9OnaZsbj15K+o4qFAMAy5bR66lTJPR2ZY29IT4nDQ3q8hqNmYwVel7fxSxutqEbk8cby45NrjkzpWxuEYbHhyczadyEbnjfIxMjiMu4pdDn5+RPW0fHi0ffP9qPwtxCpc3GJ1LZefQleSWT+zMeX5QePUCC1doKtLTQezuPvrGRxPXiRZoZ6+TRAyTeTkLf0EACfvgwiWZRkf3iYHV1ZAd70nZCz2MF586RzatWqcuyjSdPOgs9H/u5c8CxY9RjKS1Vl9dozGSs0GeJLBTlFqFvpG9ymyrrBrCOYas8aXNvwSmtkX8bwKQ9JbGSaWU5+8cc/3fr0TuNQRhtthuD4H1wD8GuxxImtbUkhOzR2wlyY+I5NM8mFs9dudJ+vwAJ8qlTwNKl6rKxGDUwTU3A/v3AmjUk/CpY6NmjtwvdrFtHWTE//Sm9v/xydVn26E+ccBb6oiIS9yNHqHHS3rzGKxkr9ACJKYsV4C10o5rUBEwXTS+DsWwPe81W+zZPmHLr0feN9in3a47/241BcCPE+84Uob/iCvJId++mEEpBgbosC/sTT9Drpk3qskuWkFi/9howOmrfgADkaTc1AQcOAGvX2petq0v2QsrK7D3pdevo9ckn6dVO6Bcvpvj/m2+S92/XuwHo+HftIqFvbLQvq9GYyWyhz5sq9HaiaR6stBPNSY93xNnjnQzdJITVzqNnO7ykhLr26E3xf7teiJfjC5NrrqHX//ov+/g8kBSzrVtpAS87L72gAHjf+5KNAnvLKlatAg4epDx2J6Fft44mej3+OLBxo33Z1aupwXnpJfLC7QZMs7OpEfnBD+j9DTfY73vzZuqBtLZqj17jncwW+ljJlEFQL+mVfSN9SjHmBoAbETcZLGF49G5CN2aP3mrf02L0Ntk8YfK+9yX/v+oq+7KlpcmB08ZGdT46c/PNlMlTUeEsmsbYOXvhKj7yEQr39PcDd99tXzY/P9kgXXaZfUgIAD72seT/V1xhX9a4rv3q1fZlNRozGS30xXnFk17p6MQoJuSE44QpnvbfN9qH0ph1P5u3874HxgaQk5WDvOzp+W0cGjGHQew8ei4zNjGGsfiYYx49Dwr3j/bb7pdtBSjsJCCQnzN9fV3+vUyL0Rcbfv6hh5zLf+Mb9Hrjjc5lb76ZXu+/3z4kBAA33UTCWVMDXHmlfdmSEuD22+n/u+5ytuP22ym18+GHncv+z/9Jr4sXOzcK3EiuXOnODo3GiC9PmAqKkrwSnO+nxGS7ZQoAEkIJOfkovt6RXlQXWc8qYTHtHekFYD+ZKDsre8oAKzcOqvKlsdIpDQjbZgXvY3BscLJRqyuzTuuY5tEnlmEQFq4uD2RnWoweAPbsoeV8VcsZGLnnHorp26VWMh/4APC3fwt8+tPOZWtrgR07nMsxjzxCDYlT7B+gxukb33DugQAUYnriCRoQdmLRImD7dgo1ZU9PytJobMlsoY+V4OjFowCcUwSNQliYW4i+ERcevcHjtcsxN4qmU+imNFaKc320ApXdejvGY+GQjZcYfe9Ir/L4eN+ZFqMHgA0bvJV3G4/OygL+8A+92+OGNWvciTHgTuCN3Huv+7LG0JdG44WMDt0YB2MnPXoH79gohCox5u2THr1NCiTv2+1gbGmsFD0jPbRfxUNHzDYbPe/iXHVPwWhzz0gPyvLLlDaXxErQPzbVo7c7Ro1GM3vJfKF36ZUaB02llJR1YyPGwNQYvZ1Hbxw0dfLoy2Jlk2LMZe3GFdzazKLeM0yNSM9ID8piaqHPVI9eo9GET2YLfaxkcrDSKXPEGLoZHh/GeHxcGdrgsm5i9FzeOGEqlh2btiY+wzH6uIyje7gbAFBRUGFZ1ij0POtVZQeLOvcWnEI3JXklU3oK2SIbseyYsrxGo5m9ZLbQG9IEncIPxtmgTl53lsiaEhbqHem1FXpj6MZpcbDSWCkkKBWUhb4833pRcqPQO3ndudm5KMgpSHr0w/ahm+K84mT6aCKX32rgVqPRzH4yW+gTYYy+kT7HwdiKfPKau4e7Jz11O4+3NFY6Wa5ruEvpdfNvGkM3qvAKkAyx9I70Tgq9KsRiJfSqxon3zft0Ct0Y5yBEvXKlRqOJlowWeqOXzqKsEkIW6q6hLscBU/6MPd6uoa7JhkJlB+/TbsYtMHXQ1ItH7xTP5/1w6KZn2CFGnzs1Rq+FXqOZu2S00BtDN5eGLgEA5hVYJ2CzUHcNd3ny6DmWbif0FfkVk79vN+PW+Js9wz3oHu6GgFCW9xK6Aahn0DPSg/H4OAbGBuxj9AaPvm+0T2fcaDRzmMwWekPo5uLgRRTkFEwuX2ymMLcQuVm55NE7xOj5s96RXvSO9EJC2oZu5hfMnxRYJ4+evezekd7JOLr5weBGG7is04xbgEI3PcM9kw2Zmxi9lBKXhi5hfsF8ZVmNRjO7yWyhN6xJc3HootKbB2iJ4HkF83Bp6JKr0A1nx3QNdQGArUc/v5BEsmuoy9VgLJAI3Yx024ZXYjkxFOUWoXOwc1K8nTx64xiEU3plXMYxPD6MzsFOVBbaLLqu0WhmNZkt9AaP/tLQpUnBVVFRUOE6dFMSI4++a7hr8rsquIG5OHTRfehmhEI3qvg8s6BoAToHO9E52EnvCxcoy3LohjNv7Dx6bgS6h7txcfCi9ug1mjlMRgu9UTSdPHqAvPKuYXehm9K8UvSNuvToEyJ5cfAiuoftvXTzYKyj0BcuQMdgB9oH2ul9kVroy/PL0TPcMzkga2dHVVEVAKC1rxVdw13ao9do5jAZLfSVhZUQEGjrb3MVZ64oqEDXUNKjtxuA5MFYNx499yRO95xG32gfFharn/psXDDNjdBXFlaiY4CEvjy/3HIFTaYsvwxD40OT3r9dj6W6mBZ0a+pomvwdjUYzN8looc/JykFVURXO9Z1zFX7gGH1bfxsWFC5QDoJy2fH4OE52nwTgzqM/2HEQALCoWP0AU56MxUJvF14BkqGb9oH2SS9cBXvwp3vouXZ2++bGiG3WQq/RzF0yWugBYHHJYpzvP49LQ5dch27O9J5BbanNQzgBLCmjh3/ub99P33Xh0U8KfYnNk6pBAtw13EUefcx96MZR6PNNQm8TuuElmrXQazSajBf6RSWLcPTiUYzFx5wHY/Mr0DPcg9M9pyeFXMWSUvp874W9yMnKsV3UrCSvBDlZOTjQfoBssvHoAaCurA7Hu46jb6TPVehmcGwQJ7tPuvboW7paAKgnYgGUdVOQU4CD7VroNZq5TuYLffEiHLt0DIB6shRTUVABCYmDHQcnhVwFNwT72vahIr/Cdh0YTt1svtRMNjl49CsqVuC9C+9BQroajAWAE90nUFVoL/TcS3nl5CuoK6tDLEe9SJkQAtXF1TjRfQIAHBtJjUYze8l4oV9ckny8kJsYPeMk9IuKFyFbZDtOljL/dm5WrqMdyyuWTw4Ir1qwyrasMcvGyaNftWAVBAR6R3pxeeXljjYbn7Cl0ys1mrlLWkIvhPi/QojDQoh9QogfCyHs3dcUMIZJnDz61QuST012itFnZ2VPNiIbF250tIM94oXFCx1XgVxRsWLy/ysX2T+U1BhScRL6wtxCLK9YDgC4bP5ltmWBZOZNUW6RckaxFWHUqyYadN3OTdL16F8AsFZKuR7AUQBfSN+kqRjDJJsWb7ItaxRVpxg9gMlFx25dcatj2Rvr6QnV/AxbO1bMI6GvLa11FG+j1+1UFgDWVNEz7dwIPadqsj0eCLxeNZGh63YOkpbQSyl/LqUcT7x9B4C9G50C7NHft+4+FOYW2pbNElmTZZw8eiD5BKhbVtziWPYPr6YHkhq9dRVcZtMi+4YJoDDPP9z2D7h5+c24tu5ax/JrF6wFAFehmxuW3gAAePyexx3LGgmjXjXRoOt2jiKl9OUPwE8AfMrm8wcA7ASws66uTrolHo/Lpw8+LYfHhl2Vf+/8e/Izz3xGjk+MO5Z95vAz8nM/+5xrWw62H5Snu087lovH4/LKf7lSfnvXt13v2y0vtrwo5391vuwY6HBVfmxiTPkZgJ0yonrVBEu6davrNTNxU69Wf4K+q0YI8SIAq6mgfyqlfCZR5k8BbAZwj3TaIYDNmzfLnTt3OhXTBMhNN92Ebdu2DQNoMX2k63WG43fd6nrNHIQQu6SUm71+L8epgJTyJocfvh/AHQA+7EYMNJnBiy++CCHEQdVFo+t15qLrVmPGUejtEELcBuBBANdLKQf9MUkTNbpeZy+6bucm6Wbd/COAEgAvCCHeE0L8sw82aaJH1+vsRdftHMQxRh/IjwrRAeCUYVMlgM7QDVEzV+xZKqVUr4vsEYt6BTLrXGaSLUCw9vhWt0KIPgBH/NhXxGRa/afCZVJK9frrCtIK3aSK+QIUQuxMZYAhKLQ9qWElLJlkeybZAmSePTYcmSF22jKDzrcSIURKo+IZvwSCRqPRaNJDC71Go9HMcjJF6L8ZtQEmtD3+kUm2Z5ItQObZo2Km2OnEbDiOlI4hksFYjUaj0YRHpnj0Go1GowmIyIVeCHGbEOKIEKJZCPFQBL+/RAjxshCiSQhxUAjxucT2eUKIF4QQxxKvzovW+2dTthBijxDip4n3y4QQ7yZseUIIoX6CeIag69XSpoyuV6c6E0LEEnY2J+yuD99Ke1wcw68JIToScwjeE0L8ZhR22iGE+K4Qol0IcUDxuRBCfD1xjPuEEPZroQP+LWqWyh+AbNB6HMsB5AHYC2B1yDYsAnBl4v8S0NKtqwH8NYCHEtsfAvDVEG36QwD/DuCnifdPAvhE4v9/BvA7UdabrtfZV69u6gzA7wL458T/nwDwRNTXWgrH8GsA/jFqWx2O4zoAVwI4oPj8dgA/AyAAXAXgXad9Ru3RbwHQLKU8LqUcBfBDAHeFaYCU8ryUcnfi/z4ATQBqEnZ8P1Hs+wDuDsMeIUQtgI8C+HbivQBwI4Cnw7YlDXS9mpgB9eqmzozn7mkAHxZOT+EJl8ivOz+QUr4G4JJNkbsA/Ksk3gFQLoSwfb5p1EJfA+CM4f3ZxLZISHRFNwJ4F0C1lPI8QKIBwPmpIP7w9wD+BEA88X4+gG6ZXEM80nPkEl2v08n0enVTZ5NlEnb3gI4jU3B73f1iIuTxtBDC+QlFmYfn+ytqobfyBiJJAxJCFAP4TwB/IKXsjciGOwC0Syl3GTdbFM30VKmMsVnXq2vc2JNpNptxY99PANRLesLWi0j2UGYSnushkiUQDJwFYGxRawGcC9sIIUQuSAwel1L+KLG5TQixSEp5PtEtag/BlGsB3CmEuB1APoBSkCdYLoTISXhRkZwjj+h6ncpMqFc3dcZlzgohcgCUwT7EEDaOxyClvGh4+y0AXw3BLr/xfH9F7dHvANCYyD7IAw3wPBumAYkY43cANEkp/87w0bMA7k/8fz+AZ4K2RUr5BSllrZSyHnQuXpJS3gfgZQAfD9OWNNH1amCG1KubOjOeu4+DjiOTPHrHYzDFsu8Ejd3MNJ4F8KuJ7JurAPRwOFJJBoww3w7KiGgBPQEn7N//AKjbsw/Ae4m/20Gxx20AjiVe54Vs1w1IZmcsB7AdQDOApwDEoq43Xa+zr16t6gzAXwC4M/F/fsLO5oTdy6O+zlI4hr8CcBCUkfMygMujttniGP4DwHkAYyDv/TMAfhvAbyc+FwAeTRzjfgCbnfapZ8ZqNBrNLCfq0I1Go9FoAkYLvUaj0cxytNBrNBrNLEcLvUaj0cxytNBrNBrNLEcLvUaj0cxytNBrNBrNLEcLvUaj0cxy/j8AoFnmCqxQmgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "ax1 = plt.subplot(2, 1, 1) # （行，列，活跃区）\n",
    "plt.plot(x, np.sin(x), 'r')\n",
    " \n",
    "ax2 = plt.subplot(2, 3, 4)\n",
    "plt.plot(x, 2 * np.sin(x), 'g')\n",
    " \n",
    "ax3 = plt.subplot(2, 3, 5, sharey=ax2)\n",
    "plt.plot(x, np.cos(x), 'b')\n",
    " \n",
    "ax4 = plt.subplot(2, 3, 6, sharey=ax2)\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 散点图\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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SIbgBIBmCGwCSIbgBIBmCGwCS+X9EcVNQ+JqJeQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#绘制折线图\n",
    "import matplotlib.pyplot as plt\n",
    "year = [2011,2012,2013,2014]\n",
    "pop = [1.2,3.4,4.5,6.5]\n",
    "#散点图绘制函数\n",
    "plt.scatter(year,pop)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 直方图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
